Image by Marvin Meyer
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THE TEAM

It’s an exciting time at Twin Dynamics as we build a challenger brand in the simulation space. We’re looking for passionate and ambitious people with tonnes of grit, who want to play a part in bringing science fiction to life.

DR NOUKHEZ AHMED

Managing Director and Co-founder

Dr Noukhez Ahmed is the Managing Director and Co-Founder of Twin Dynamics. He's based in the company's headquarter in Barnsley, UK. Noukhez has spent the past four years building Twin Dynamics (formerly called HMU Design Engineering) into the digital transformation disruptor that it is today. From early beginnings, Noukhez has applied to IoT Tribe North Accelerator program and brought a new concept of Physics based Digital Twin. 

 

Noukhez has also successfully led numerous academic and commercial projects while at the University of Huddersfield and Twin Dynamics. Noukhez has completed his Doctor of Philosophy from University of Huddersfield in Performance Evaluation and Optimisation of Vaneless Diffuser Of Various Shapes for a Centrifugal Compressor. He holds immense research expertise in Computational Fluid Dynamics (CFD) particularly in monitoring different fluids and particles behaviours. He also contributed towards developing in-house machine learning code for Digital Twin technology, which computes asset operational prognosis and develops appropriate preventive maintenance solutions.

 

Noukhez has over 9 years of expertise in fluid dynamics (internal and external), thermal & structural analysis and data analysis using machine learning and advanced analytics. He has worked with design optimisation techniques and New Product Development (NPD). He has also expertise in 1D analysis in turbomachines. Before co-founding Twin Dynamics, he worked as a research scientist and university lecturer at University of Huddersfield. Noukhez is also currently working as a researcher at University of Wolverhampton.

DR SHRAWASTI SAHARE

Director and Co-founder

Dr Shrawasti Sahare is the Director and Co-Founder of Twin Dynamics. He's based in the company's headquarter in Barnsley, UK. He is using is Data Scientist skills and expertise in developing and enhancing Physics Based Digital Twin. He was majorly involved in developing Physics based Digital Twin algorithms. He was part of Pitch-In project and Innovate UK grant. He has adapted the Digital Twin tech with the team to integrate real-time sensors data with airborne transmission effect using Machine Learning codes. 

 

Shrawasti has over 5 years working experience in developing cutting edge technology with recent contribution in developing in-house machine learning code for Digital Twin technology. He holds immense research expertise in Computational Fluid Dynamics (CFD) particularly in monitoring different gases and particles behaviour such as air pollutants. He has over 4 years of experience in developing in-house fluid dynamics mathematical modelling codes. Furthermore, he has also developed an in-house fluid dynamic solver code based on molecular Lattice Boltzmann Method. He has extensively applied machine learning to fluid dynamics problems. His most recent work at University of Huddersfield during his Doctor of Philosophy, is to develop inverse design framework for functional surfaces to be used in aerodynamic applications. He was also a University teacher and has various research publications.